Azure Table Storage vs. Google Cloud Bigtable vs. Oracle NoSQL Database vs. Python Comparison Chart

Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores—on-premises or cloud-based—Table storage lets you scale up without having to manually shard your dataset. Availability also isn’t a concern: using geo-redundant storage, stored data is replicated three times within a region—and an additional three times in another region, hundreds of miles away. Table storage is excellent for flexible datasets—web app user data, address books, device information, and other metadata—and lets you build cloud applications without locking down the data model to particular schemas. Because different rows in the same table can have a different structure—for example, order information in one row, and customer information in another—you can evolve your application and table schema without taking it offline. Table storage embraces a strong consistency model.

Oracle NoSQL Database is designed to handle high-volume, high-velocity data applications requiring low-latency responses and flexible data models. It supports JSON, table, and key-value data types, and operates both on-premise and as a cloud service. The database scales elastically to meet dynamic workloads and provides distributed data storage across multiple shards, ensuring high availability and rapid failover. It includes Python, Node.js, Java, C, C#, and REST API drivers for easy application development. Additionally, it integrates with Oracle products such as IoT, Golden Gate, and Fusion Middleware. Oracle NoSQL Database Cloud Service is a fully managed service, freeing developers from backend infrastructure management. Oracle NoSQL Database Cloud Service is a fully managed database service for developers who want to focus on application development without dealing with the hassle of managing the back-end hardware and software infrastructure.